The thesis became the company.

Hanaska started with a master's thesis in economics and a simple question: are prediction markets actually accurate?

The plan was straightforward — collect orderbook data, run some regressions, write a paper. But the data had other ideas. Early models suggested we'd found something real: a calibration edge, divergences between prediction markets and options markets that seemed exploitable. The kind of finding you want to be true.

But as we kept collecting data and pushing the models harder with proper statistical rigor, the story changed. The edge narrowed. The markets proved more accurate than we'd expected. What looked like signal started looking like noise at the margins.

That humbling result turned out to be more valuable than any alpha signal ever could have been.

Instead of walking away, we became fascinated — with the microstructure beneath the prices, with how these markets aggregate information from thousands of participants in real time, and with how prediction market probabilities interact with and sometimes lead the rest of the financial world.

For Will, this was a natural extension of a lifelong obsession with markets. Stocks, options, commodities — it was never really about the prices themselves. It was always about the structure underneath. Why does a seller decide to sell at exactly this moment? Why does a buyer step in here and not there? How do millions of individual decisions — each made with incomplete information and competing motivations — combine to produce something that looks, surprisingly often, like the truth? That question has driven everything.

Prediction markets put that structure front and center in a way few other instruments do. And when you layer them against options markets, equity flows, commodity data, and macro — the picture gets richer. The disagreements get more interesting. The signal gets cleaner.

What started as a thesis became a company. And the goal now is bigger than finding mispricings.

We're building toward a live terminal that surfaces the real-time relationship between prediction markets and financial markets — intelligence that doesn't exist anywhere else in one place. Advising Fortune 100 companies on timing and risk using market-derived probability. Helping organizations build and calibrate internal prediction markets to forecast their own futures. And eventually becoming one of the most trusted predictive analytics platforms in the industry.

The markets told us something when we pushed hard enough. We're still listening.